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---
license: apache-2.0
datasets:
- databricks/databricks-dolly-15k
language:
- en
pipeline_tag: text-generation
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T
---
TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T finetuned using dolly dataset.
Training took 1 hour on an 'ml.g5.xlarge' instance.
```python
hyperparameters ={
'num_train_epochs': 3, # number of training epochs
'per_device_train_batch_size': 6, # batch size for training
'gradient_accumulation_steps': 2, # Number of updates steps to accumulate
'gradient_checkpointing': True, # save memory but slower backward pass
'bf16': True, # use bfloat16 precision
'tf32': True, # use tf32 precision
'learning_rate': 2e-4, # learning rate
'max_grad_norm': 0.3, # Maximum norm (for gradient clipping)
'warmup_ratio': 0.03, # warmup ratio
"lr_scheduler_type":"constant", # learning rate scheduler
'save_strategy': "epoch", # save strategy for checkpoints
"logging_steps": 10, # log every x steps
'merge_adapters': True, # wether to merge LoRA into the model (needs more memory)
'use_flash_attn': True, # Whether to use Flash Attention
}
``` |